Network medicine: facilitating a new view on complex diseases
Journal article, 2023

Complex diseases are prevalent medical conditions which are characterized by inter-patient heterogeneity with regards to symptom profiles, disease trajectory, comorbidities, and treatment response. Their pathophysiology involves a combination of genetic, environmental, and psychosocial factors. The intricacies of complex diseases, encompassing different levels of biological organization in the context of environmental and psychosocial factors, makes them difficult to study, understand, prevent, and treat. The field of network medicine has progressed our understanding of these complex mechanisms and highlighted mechanistic overlap between diagnoses as well as patterns of symptom co-occurrence. These observations call into question the traditional conception of complex diseases, where diagnoses are treated as distinct entities, and prompts us to reconceptualize our nosological models. Thus, this manuscript presents a novel model, in which the individual disease burden is determined as a function of molecular, physiological, and pathological factors simultaneously, and represented as a state vector. In this conceptualization the focus shifts from identifying the underlying pathophysiology of diagnosis cohorts towards identifying symptom-determining traits in individual patients. This conceptualization facilitates a multidimensional approach to understanding human physiology and pathophysiology in the context of complex diseases. This may provide a useful concept to address both the significant interindividual heterogeneity of diagnose cohorts as well as the lack of clear distinction between diagnoses, health, and disease, thus facilitating the progression towards personalized medicine.

network medicine

multidimensional patient characterization

nosology

complex diseases

pathophysiology

Author

Marija Cvijovic

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

University of Gothenburg

Annikka Polster

Chalmers, Life Sciences, Systems and Synthetic Biology

Frontiers in Bioinformatics

26737647 (eISSN)

Vol. 3 1163445

Subject Categories

Public Health, Global Health, Social Medicine and Epidemiology

DOI

10.3389/fbinf.2023.1163445

More information

Latest update

4/23/2024